van der Post et al. (2012) support the classification table

Van der Post and colleagues studied lack of social support as a possible predictor of emergency compulsory admission. For a random sample of 252 patients (netto n=244) of two psychiatric emergency teams, data were collected on social networks, social interactions and the number of emergency compulsory admissions during a two-year follow-up period.

The researchers concluded that of the social support variables, living alone was the only predictor of emergency compulsory admission and readmission. Patients who lived alone had fewer people in their social network (4.6 versus 6.1, p ≤.001) compared with patients who lived with others.

Among patients who lived alone, the percentage of patients with a compulsory admission was significantly higher among the patients with a high score for negative interactions than among patients with a low score (34% versus 13%, p≤.05).

However, the stepwise logistic regression analyses does not support these conclusions.

Firstly, the model does not include a 'domestic situation' * 'negative exchanges' interaction term. Thus, the multiple logistic regression analysis does not show that a high level of negative social interactions increased the risk of compulsory admission among patients who lived alone.

Secondly, the authors observe that in the final logistic regression model differences in network size is not a significant factor. This suggests that the difference of 1.5 person(s) in the bivariate analysis was relevant. However, overall the average network included just over 5 persons. It is difficult to understand who in the 1.5 difference in the bivariate analysis could be the 'significant others'.

Thirdly, the effect of 'living alone' is not evaluated in the context of the model. Based on the model the compulsory admission odds ratio is estimated to be almost three times higher for patients living alone than for patients living with others. Note that less than 1 out of five patients in this setting is involuntarily admitted. The authors report a high percentage of correctly predicted cases: 82%. This percentage, however, is inflated because the same data was used to estimate and to evaluate the model (read here why generally the classification table is not very helpful). More importantly, the overall probability of being involuntary (re)admitted was .17 in this sample. Therefore, 82% correctly predicted shows that the logistic model has no predictive power. Poor model fit is also illustrated in the low Nagelkerke-value (.11).

To understand the difference between voluntary or involuntary admission, these results are of no practical importance because the model does not fit the data. But then these results would have been of no practical importance if the model had fitted because it is difficult to prevent that people live alone.

Months after Van der Post's defense of his PhD-thesis (January 2012) the paper was published in Psychiatric Services. In a long letter to the promotors I had questioned the scientific quality of the thesis. Some changes were made, but we left it at that. Later I came across the publication and informed the journal's editor that the reviewers had missed a point (or two). Professor Howard Goldman responded:

"Thank you for calling this issue to our attention. I am sorry that it did not arise in the review process. It is now too late for us to publish another letter with a response on this matter, and we hope that readers very familiar with the details of this research will consult your website."

Lets hope that readers NOT very familiar with the details of this research will also take an interest in these issues.